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What is success independent samples design?
different samples of respondents from the population complete the survey over a time period
What is a stratified random sample survey?
A stratified random sample survey is a sampling method that involves dividing a population into distinct subgroups, or strata, based on specific characteristics such as age, gender, or income level. Researchers then randomly select samples from each stratum to ensure that the sample reflects the diversity of the entire population. This approach enhances the representativeness of the survey results and allows for more accurate comparisons between different subgroups. It is particularly useful when certain segments of the population might otherwise be underrepresented in a simple random sample.
What type of sampling uses a fair representation of the population?
Stratified sampling is a type of sampling that uses a fair representation of the population by dividing the population into different subgroups or strata and then selecting samples from each stratum in proportion to their size in the population. This method helps ensure that all groups in the population are adequately represented in the final sample.
If there are 3 different samples from a set population can you get 3 different values for the same statistic?
Yes you can.
What is the distinguish between systematic and tratified sampling?
Systematic sampling involves selecting samples from a larger population at regular intervals, typically using a fixed sampling interval (e.g., every 10th person on a list). In contrast, stratified sampling divides the population into distinct subgroups or strata based on shared characteristics (like age or income) and then randomly samples from each stratum to ensure representation. While systematic sampling is straightforward and efficient, stratified sampling ensures that specific subgroups are adequately represented in the sample, potentially leading to more accurate and generalizable results.
What is the example of sample design?
An example of sample design is stratified sampling, where a population is divided into distinct subgroups, or strata, based on specific characteristics such as age, income, or education level. Researchers then randomly select samples from each stratum to ensure that the sample accurately reflects the diversity of the entire population. This method helps improve the precision of the results and allows for more detailed analysis of different segments within the population.
How do you select random samples in statistics?
To select random samples in statistics, you can use methods such as simple random sampling, systematic sampling, stratified sampling, or cluster sampling. Simple random sampling involves selecting individuals from a population where each has an equal chance of being chosen, often using random number generators. Systematic sampling selects every nth individual from a list, while stratified sampling divides the population into subgroups and samples from each. Cluster sampling involves dividing the population into clusters, then randomly selecting entire clusters to include in the sample.
How many different simple random samples of size 4 can be obtained from a population whose size is 42?
Number of samples = 42C4 = 42*41*40*39/24 = 111930
What is stratified sampling under research methodology?
Stratified sampling is a sampling method in research where the population is divided into subgroups or strata based on certain characteristics. Samples are then selected from each stratum in proportion to the population, to ensure representation of all groups. This method helps to reduce sampling errors and improves the accuracy of the research findings.
How many different samples of size 4 can be selected from a population of size 8?
To determine the number of different samples of size 4 that can be selected from a population of size 8, you can use the combination formula, which is given by ( C(n, k) = \frac{n!}{k!(n-k)!} ). Here, ( n = 8 ) and ( k = 4 ). Thus, the number of samples is ( C(8, 4) = \frac{8!}{4!(8-4)!} = \frac{8!}{4!4!} = 70 ). Therefore, there are 70 different samples of size 4 that can be selected from a population of size 8.
What is the definition of dependent sample?
two samples are independent if they are drawn from two different populations, and/ or the samples have no effect on each other. eg: We want to estimate the difference between the mean salaries of all male and all female executives. We draw one sample from the population of male executives and another from the population of female executives. These two samples are independent because they come from different populations and the samples have no effect on each other Rate This Answer
How many different samples of size 3 (with replacement) can be taken from a finite population of size 10?
When sampling with replacement from a finite population, each selection is independent. For a population of size 10, each of the 3 selections can be any of the 10 elements. Therefore, the total number of different samples of size 3 that can be taken is (10^3 = 1000).
